bioRxivMicrobiologyPreprint
Prophages in the infant gut are largely induced, and may be functionally relevant to their hosts.
T. A. Redgwell, J. Thorsen, M.-A. Petit, L. Deng, G. A. Vestergaard, J. Russel, H. Bisgaard, D. S. Nielsen, S. J. Sorensen, J. Stokholm, S. A. Shah
Abstract
BackgroundBacteriophages are the most abundant biological entity on the planet, and are key components of any ecosystem they are present in. The gut virome is increasingly being implicated in disease states although these studies largely focus on lytic phages in adults. Here we identify prophages from a large infant cohort and investigate their potential functions. ResultsWe identified 10645 vOTUs from 662 metagenomes. No core virome was found: the most prevalent vOTU was identified in 70% of the samples. The most abundant and prevalent group of phages are a novel group closely related to Bacteroides phage Hanky p00. Functional annotation of this group revealed the presence of genes in the dDTP-L-rhamnose pathway, possibly involved in the production of capsular polysaccharides. We also found an abundance of diversity generating retroelements in the phages. Additionally, paired virome data allowed us to show that the majority of prophages are induced in at least one sample and that this is not affected by the use of antibiotics in the 4 weeks prior to sampling. ConclusionsProphages in the infant gut are largely unique to the individual and not shared. Most of them appear to be induced and so may be key drivers in shaping the bacterial microbiome. The most abundant group of phages are novel, and possess elements that may allow them to maintain differentially susceptible subpopulations of their host bacterium; whilst also containing diversity generating retroelements that could expand their host range. Prophages are important components of the infant gut that may have far reaching influences on the composition and function of the microbiome.
- organism: human
- assay: metagenomics
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: experimental assay
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